Text Classification
setfit
Safetensors
sentence-transformers
English
bert
transaction-classification
banking
finance
few-shot-learning
contrastive-learning
Eval Results (legacy)
text-embeddings-inference
Instructions to use maaz-zaidi/transaction-classifier-setfit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use maaz-zaidi/transaction-classifier-setfit with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("maaz-zaidi/transaction-classifier-setfit") - sentence-transformers
How to use maaz-zaidi/transaction-classifier-setfit with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("maaz-zaidi/transaction-classifier-setfit") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9b6294c440b82e0ff94d7ccba560963a4858234eb91ab3d43f1c6123205408ff
- Size of remote file:
- 31.7 kB
- SHA256:
- 6e693e8c82771bad76c38aa78d14d7c4199eccd4eddf0546222788f4467184fe
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